code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 238 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 238 | 1 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list[list[int | float]] ):
"""simple docstring"""
lowerCamelCase__ : Dict =len(__lowerCamelCase )
lowerCamelCase__ : List[Any] =len(matrix[0] )
lowerCamelCase__ : str =min(__lowerCamelCase , __lowerCamelC... | 238 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def snake_case__ ( __lowerCamelCase : np.ndarray ):
"""simple docstring"""
lowerCamelCase__ , lowerCamelCase__ : Tuple =np.shape(__lowerCamelCase )
if rows != columns:
lowerCamelCase__ : st... | 238 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : Any =extended_euclid(__lowerCamelCas... | 238 | 1 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
_lowercase : List[Any] = "\\n@misc{chen2021evaluating,\n... | 238 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_P... | 238 | 1 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Union[str, Any], lowerCamelCase : list[int] )-> None:
lowerCamelCase__ : Dict =len(lowerCamelCase )
lowerCamelCase__ : str =[0] * l... | 238 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
_lowercase : Union[str, Any] = [True] * 1_0_0_0_0_0_1
_lowercase : Any = 2
while i * i <= 1_0_0_0_0_0_0:
if seive[i]:
for j in range(i * i, 1_0_0_0_0_0_1, i):
_lowercase : Any = False
i += ... | 238 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_lowercase : Any = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__... | 238 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision... | 238 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : List[Any] , __lowerCam... | 238 | 1 |
"""simple docstring"""
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.m... | 238 |
"""simple docstring"""
from functools import lru_cache
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =2
lowerCamelCase__ : Optional[int] =set()
while i * i <= n:
if n % i:
i += 1
else:
... | 238 | 1 |
"""simple docstring"""
import argparse
import os
import re
_lowercase : Optional[Any] = "src/transformers"
# Pattern that looks at the indentation in a line.
_lowercase : List[str] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercas... | 238 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Optional[int] = "▁"
_lowercase : Optional[Any] ... | 238 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowerc... | 238 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : List[Any] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas... | 238 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaP... | 238 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAP... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : List[Any], lowerCamelCase : Any )-> Tuple:
lowerCamelC... | 238 |
"""simple docstring"""
def snake_case__ ( ):
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowercase : str = generate_large_matrix()
_lowercase : str = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1... | 238 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : List[str] = logging.get_logger(__name__)
_lowercase : Tuple = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/conf... | 238 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class _... | 238 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffuser... | 238 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
_lowercase : Dict = "2020.9.26"
_lowercase : Union[str, Any] = "xcodz-dot, cclaus, dhruvmanila"
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float ... | 238 |
"""simple docstring"""
import argparse
import os
import re
_lowercase : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
_lowercase : List[Any] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : int ... | 238 | 1 |
"""simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 238 |
"""simple docstring"""
from __future__ import annotations
_lowercase : Dict = 1.6_021E-19 # units = C
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , ):
"""simple docstring"""
if (c... | 238 | 1 |
"""simple docstring"""
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class __SCREAMING_SNAKE_CASE ( ... | 238 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_mode... | 238 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowercase : Optional[Any] = logging.get_logger(__name__)
class __SCREAMING_SNAK... | 238 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fr... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
f... | 238 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Dict, lowerCamelCase : list )-> None:
lowerCamelCase__ : Tuple =set_counts
lowerCamelCase__ : Dict =max(lowerCamelCase )
lo... | 238 | 1 |
"""simple docstring"""
_lowercase : dict[tuple[int, int, int], int] = {}
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
# if we are absent twice, or late 3 consecutive da... | 238 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 238 | 1 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as... | 238 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTo... | 238 | 1 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : int = 1000 ):
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 238 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch... | 238 | 1 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list[int] , __lowerCamelCase : list[int] ):
"""simple docstring"""
# Check if the input is valid
if not len(__lowerCamelCase ) == len(__lowerCamelCase ) == 3:
raise ValueError('''Please enter a valid equati... | 238 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 238 | 1 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def snake_case__ ( __lowerCamelCase : str ):
"""simple docstring"""
def decorator(__lowerCamelCase : str ):
lowerCamelCase__ : int =getattr(__lowerCamelCase , '''handle_k... | 238 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 238 | 1 |
"""simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowercase : str = g... | 238 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : Any =extended_euclid(__lowerCamelCas... | 238 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 238 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_P... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[Any], lowerCamelCase : int )-> None:
lowerCamelCase__ : List[Any] ... | 238 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.... | 238 | 1 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : str , __lowerCamelCase : bool = False ):
"""simple docstring"""
if not isinstance(__lowerCamelCase , __lowerCamelCase ):
lowerCamelCase__ : List[Any] =f'''Expected string as input, found {type(__low... | 238 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_lowercase : Any = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__... | 238 | 1 |
"""simple docstring"""
from torch import nn
class __SCREAMING_SNAKE_CASE ( nn.Module ):
'''simple docstring'''
def __init__( self : List[str], lowerCamelCase : List[Any], lowerCamelCase : List[str] )-> Union[str, Any]:
super().__init... | 238 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : List[Any] , __lowerCam... | 238 | 1 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 238 |
"""simple docstring"""
from functools import lru_cache
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =2
lowerCamelCase__ : Optional[int] =set()
while i * i <= n:
if n % i:
i += 1
else:
... | 238 | 1 |
"""simple docstring"""
_lowercase : str = {
0: "0",
1: "1",
2: "2",
3: "3",
4: "4",
5: "5",
6: "6",
7: "7",
8: "8",
9: "9",
1_0: "a",
1_1: "b",
1_2: "c",
1_3: "d",
1_4: "e",
1_5: "f",
}
def snake_case__ ( __lowerCame... | 238 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Optional[int] = "▁"
_lowercase : Optional[Any] ... | 238 | 1 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
_lowercase : Tuple = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n jo... | 238 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : List[Any] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas... | 238 | 1 |
"""simple docstring"""
def snake_case__ ( __lowerCamelCase : list ):
"""simple docstring"""
if any(not isinstance(__lowerCamelCase , __lowerCamelCase ) or x < 0 for x in sequence ):
raise TypeError('''Sequence must be list of non-negative integers''' )
for _ in range(len(__... | 238 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAP... | 238 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_robert... | 238 |
"""simple docstring"""
def snake_case__ ( ):
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowercase : str = generate_large_matrix()
_lowercase : str = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1... | 238 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Optional[int] = "▁"
_lowercase : Optional[Any] ... | 238 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class _... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : list[int] ):
"""simple docstring"""
return len(set(__lowerCamelCase ) ) == len(__lowerCamelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 238 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_... | 238 | 1 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = ... | 238 |
"""simple docstring"""
import argparse
import os
import re
_lowercase : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
_lowercase : List[Any] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : int ... | 238 | 1 |
"""simple docstring"""
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
... | 238 |
"""simple docstring"""
from __future__ import annotations
_lowercase : Dict = 1.6_021E-19 # units = C
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , ):
"""simple docstring"""
if (c... | 238 | 1 |
"""simple docstring"""
from __future__ import annotations
import pandas as pd
def snake_case__ ( __lowerCamelCase : list[int] , __lowerCamelCase : list[int] , __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Tuple =[0] * no_of_process... | 238 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_mode... | 238 | 1 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxT... | 0 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fr... | 238 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : str ) -> bool:
'''simple docstring'''
return credit_card_number.startswith(("34", "35", "37", "4", "5", "6") )
def lowerCAmelCase_ ( snake_case_ : str ) -> bool:
'''simple docstr... | 1 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Dict, lowerCamelCase : list )-> None:
lowerCamelCase__ : Tuple =set_counts
lowerCamelCase__ : Dict =max(lowerCamelCase )
lo... | 238 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from tran... | 2 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 238 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
... | 3 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTo... | 238 | 0 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__snake_case =3
def a_ ( lowerCamelCase : int ):
print('Generating primitive root of p' )
while True:
lowerCAmelCas... | 4 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch... | 238 | 0 |
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 5 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 238 | 0 |
from __future__ import annotations
def __lowerCAmelCase ( a__ , a__ ) -> list[int]:
__a = 0
__a = len(a__ ) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nums[i] + nums[j] < target:
__a ... | 6 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 238 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ : int = 10**12 ) -> int:
'''simple docstring'''
A__ = 1
A__ = 0
A__ = 1
A__ = 1
while numerator <= 2 * min_total - 1:
prev_numerator += 2 * ... | 7 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : Any =extended_euclid(__lowerCamelCas... | 238 | 0 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCAmelCase_ = logging.get_logger(__name__)
class snake_case_ ( __A ):
'''simple docstring'''
def __init__( self : Tuple , *_Upper... | 8 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_P... | 238 | 0 |
from importlib import import_module
from .logging import get_logger
__lowerCAmelCase : str =get_logger(__name__)
class _lowercase :
'''simple docstring'''
def __init__( self :List[Any] , lowerCAmelCase__ :List[Any] , lowerCAmelCase__ :str=None ) -> int:
... | 9 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.... | 238 | 0 |
def lowerCAmelCase_ ( __a = 1000 ) -> int:
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 10 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_lowercase : Any = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__... | 238 | 0 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 11 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : List[Any] , __lowerCam... | 238 | 0 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.utils imp... | 12 |
"""simple docstring"""
from functools import lru_cache
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =2
lowerCamelCase__ : Optional[int] =set()
while i * i <= n:
if n % i:
i += 1
else:
... | 238 | 0 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Arr... | 13 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Optional[int] = "▁"
_lowercase : Optional[Any] ... | 238 | 0 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 14 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : List[Any] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas... | 238 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def UpperCAmelCase ( a_ ) -> str:
"""simple docstring"""
__A = {}
__A = job["started_at"]
__A = job["completed_at"]
__A = date_parser.parse(a_ )
... | 15 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAP... | 238 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokeniz... | 16 |
"""simple docstring"""
def snake_case__ ( ):
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowercase : str = generate_large_matrix()
_lowercase : str = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1... | 238 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_a = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViTOnnxConf... | 17 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class _... | 238 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__lowerCamelCase : List[str] = re.compile(R'''\b(a|an|the)\b''', re.UNICODE)
__lowerCamelCase : Dict = None
def _snake_case ( ):
"""simple docstring"""
SCREAMIN... | 18 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_... | 238 | 0 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.models... | 19 |
"""simple docstring"""
import argparse
import os
import re
_lowercase : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
_lowercase : List[Any] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : int ... | 238 | 0 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXT... | 20 |
"""simple docstring"""
from __future__ import annotations
_lowercase : Dict = 1.6_021E-19 # units = C
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , ):
"""simple docstring"""
if (c... | 238 | 0 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE : Optional[int] = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n a... | 21 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_mode... | 238 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 22 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fr... | 238 | 0 |
'''simple docstring'''
import os
import numpy
import onnx
def snake_case_ ( _lowerCAmelCase : str , _lowerCAmelCase : Optional[Any] ) -> int:
UpperCAmelCase : Tuple = a.name
UpperCAmelCase : Optional[Any] = b.n... | 23 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Dict, lowerCamelCase : list )-> None:
lowerCamelCase__ : Tuple =set_counts
lowerCamelCase__ : Dict =max(lowerCamelCase )
lo... | 238 | 0 |
def lowerCamelCase__ ( snake_case_ : int , snake_case_ : str ) -> Tuple:
__snake_case = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def lowerCamelCase__ ( snake_case_ : Li... | 24 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 238 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class lowerCAmelCase_ :
"""simple docstring"""
__UpperCamelCase : int
__UpperCamelCase : TreeNode | None ... | 25 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTo... | 238 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
_snake_case = logging.get_logger(__name__)
_snake_case = {
"Intel/dpt-large": "https://huggingface.co/Intel/dpt-large/resolve/main/config.json",
# See a... | 26 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch... | 238 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_c... | 27 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 238 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase : Tuple = {
"configuration_blip": [
"BLIP_PRETR... | 28 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 238 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'asapp/sew-tiny-100k': 'https://huggingface.co/asapp/sew-tiny-100k/resolve/main/c... | 29 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : Any =extended_euclid(__lowerCamelCas... | 238 | 0 |
def a ( snake_case__: int = 1_000 ):
'''simple docstring'''
lowercase_ = 2**power
lowercase_ = 0
while n:
lowercase_ , lowercase_ = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(inp... | 30 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_P... | 238 | 0 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
__SCREAMI... | 31 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.... | 238 | 0 |
from manim import *
class SCREAMING_SNAKE_CASE__ ( lowercase__ ):
def SCREAMING_SNAKE_CASE ( self : Any ) -> Optional[int]:
a_ : Optional[int] = Rectangle(height=0.5 , width=0.5 )
a_ : List[Any] = R... | 32 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_lowercase : Any = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__... | 238 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A : str = logging.get_logger(__name__)
... | 33 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : List[Any] , __lowerCam... | 238 | 0 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _a ( __a ... | 34 |
"""simple docstring"""
from functools import lru_cache
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =2
lowerCamelCase__ : Optional[int] =set()
while i * i <= n:
if n % i:
i += 1
else:
... | 238 | 0 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase ) -> bool:
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
snake_case__ : Tuple = sorted(string.lower() )
return len(_lowerC... | 35 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Optional[int] = "▁"
_lowercase : Optional[Any] ... | 238 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, lo... | 36 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : List[Any] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas... | 238 | 0 |
'''simple docstring'''
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowerCAmelCase = TypeVar('''T''')
class lowerCAmelCase_( Generic... | 37 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAP... | 238 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import... | 38 |
"""simple docstring"""
def snake_case__ ( ):
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowercase : str = generate_large_matrix()
_lowercase : str = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1... | 238 | 0 |
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
_a = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
_a = [ord(letter) for letter in string.ascii_lowercase]
_a = {ord(char)... | 39 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class _... | 238 | 0 |
"""simple docstring"""
# Function to print upper half of diamond (pyramid)
def lowercase ( A_ )-> List[Any]:
'''simple docstring'''
for i in range(0 , A_ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(" " , ... | 40 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_... | 238 | 0 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
_A : Optional[int] ='''<<<<<<< This should probably be modified be... | 41 |
"""simple docstring"""
import argparse
import os
import re
_lowercase : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
_lowercase : List[Any] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : int ... | 238 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class __UpperCAmelCase ( unittest.... | 42 |
"""simple docstring"""
from __future__ import annotations
_lowercase : Dict = 1.6_021E-19 # units = C
def snake_case__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , ):
"""simple docstring"""
if (c... | 238 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
... | 43 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_mode... | 238 | 0 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 44 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fr... | 238 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impor... | 45 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Dict, lowerCamelCase : list )-> None:
lowerCamelCase__ : Tuple =set_counts
lowerCamelCase__ : Dict =max(lowerCamelCase )
lo... | 238 | 0 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRo... | 46 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 238 | 0 |
'''simple docstring'''
lowerCamelCase : Optional[Any] = 2_5_6
# Modulus to hash a string
lowerCamelCase : int = 1_0_0_0_0_0_3
def _lowerCAmelCase ( _UpperCamelCase : str , _UpperCamelCase : str ) -> bool:
"""simple docstring"""
... | 47 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTo... | 238 | 0 |
# Algorithm for the pigeonhole sorting
def A ( _SCREAMING_SNAKE_CASE ) -> List[Any]:
lowerCamelCase : Any = min(_SCREAMING_SNAKE_CASE ) # min() finds the minimum value
lowerCamelCase : Union[str, Any] = max(_SCREAMING_SNAKE_CASE ) # ... | 48 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch... | 238 | 0 |
import qiskit
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase ):
__a = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
__a = qiskit.QuantumCircuit(_UpperCAmelCase , _UpperCAmelCase )
# Map ... | 49 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 238 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
... | 50 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 238 | 0 |
def A (__A : str , __A : str ) -> str:
"""simple docstring"""
UpperCAmelCase_ = len(__A )
UpperCAmelCase_ = len(__A )
UpperCAmelCase_ = (
first_str_length if first_s... | 51 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : Any =extended_euclid(__lowerCamelCas... | 238 | 0 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, val... | 52 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_P... | 238 | 0 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import C... | 53 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.... | 238 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : int = {
'''configuration_blenderbot_small''': [
... | 54 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_lowercase : Any = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__... | 238 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 55 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : List[Any] , __lowerCam... | 238 | 0 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class a ( nn.Module ):
snake_case_ = 42
snake_case_ = jnp.floataa
def A_ ( self : int ):
snake_case_ = nn.Conv(
self.out_channels , ... | 56 |
"""simple docstring"""
from functools import lru_cache
def snake_case__ ( __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : Optional[Any] =2
lowerCamelCase__ : Optional[int] =set()
while i * i <= n:
if n % i:
i += 1
else:
... | 238 | 0 |
"""simple docstring"""
def _lowerCamelCase ( ):
'''simple docstring'''
__lowerCAmelCase = []
__lowerCAmelCase = 1
while len(_UpperCamelCase ) < 1e6:
constant.append(str(_UpperCamelCase ) )
i += 1
__lowerCAmelCase = "".join(_UpperCamelCase... | 57 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase : Optional[int] = "▁"
_lowercase : Optional[Any] ... | 238 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 58 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : List[Any] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas... | 238 | 0 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
__lowerCamelCase = ["""small""", """medium""", """large"""]
__lowerCamelCase = """lm_head.decoder.weight"""
__lowerCamelCase = """lm_head.weight"""
def UpperCamelCase ( ... | 59 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAP... | 238 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
snake_case__ : int = logging.get_logger(__name__)
snake_case__ : i... | 60 |
"""simple docstring"""
def snake_case__ ( ):
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowercase : str = generate_large_matrix()
_lowercase : str = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1... | 238 | 0 |
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